3D Point Cloud Decoding With Adaptive Node Prediction
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Solution Overview
Problem
Existing encoding methods for three-dimensional data, such as point cloud data, face challenges in improving encoding efficiency.
Innovation Solution
Adaptive use of inter prediction, intra prediction, or no prediction on current nodes within a coding unit, combined with hierarchical transform processing, to determine and apply the appropriate prediction method based on the depth in an octree structure, optimizing encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If point cloud data is compressed using existing encoding methods, then the amount of three-dimensional data is reduced for accumulation and transmission, but encoding efficiency needs improvement
Solution Approach 1:
The current coding unit is divided into multiple current nodes, and prediction processing is performed independently on each current node. This segmentation allows for more granular and adaptive compression, improving encoding efficiency while maintaining data quality.
Solution Approach 2:
The patent dynamically selects between inter prediction, intra prediction, or no prediction for each current node based on its characteristics. This dynamic adaptation optimizes the compression ratio for each node, thereby improving overall encoding efficiency.
2Measurement precision
If hierarchical transform processing is applied to attribute values, then encoding precision is improved, but processing complexity increases
Solution Approach 1:
The attribute values are processed through hierarchical transform in a segmented manner across different levels of the octree structure. This allows precision to be improved at critical levels while avoiding unnecessary complexity at other levels.
Solution Approach 2:
Hierarchical transform processing is applied selectively based on the local characteristics of each current node. This ensures that processing complexity is incurred only where it provides the most benefit to encoding precision.
3Productivity
If adaptive prediction methods are used on current nodes, then encoding efficiency is improved, but determination complexity increases
Solution Approach 1:
The determination of prediction method is performed independently for each current node, allowing simple local decisions rather than complex global optimization. This segmentation of the decision-making process improves encoding efficiency without excessive complexity.
Solution Approach 2:
Each current node essentially determines its own optimal prediction method based on its local characteristics, reducing the need for complex centralized control and simplifying the overall determination process.
Data Source
AI summary
A decoding method includes: determining whether one of inter prediction, intra prediction, or no prediction is to be performed on a current node that is included in a current coding unit; and performing (i) the one of the inter prediction, the intra prediction, or no prediction determined and (ii) inverse hierarchical transform processing on the current node to calculate an attribute value of a three-dimensional point that is included in the current coding unit. The current node has a coefficient that is generated by hierarchical transform processing by an encoding device. The attribute value is transformed to the coefficient in the hierarchical transform processing. The coefficient is transformed to the attribute value in the inverse hierarchical transform processing.